ElectroMagnetoEncephalography Software: Overview and Integration with Other EEG/MEG Toolboxes

Peyk, Peter; Cesarei, Andrea De; Junghöfer, Markus

doi:10.1155/2011/861705

Cited by 226 publications

(179 citation statements)

References 14 publications

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“…Off-line analysis was performed using EMEGS (freely available at http://www.emegs.org/) (Peyk et al, 2011) and included filtering (0.1 Hz high-pass and 40 Hz low-pass), removal of eye movement artifacts (Schlögl et al, 2007), artifact detection and sensor interpolation, and average reference. A baseline correction based on the 100 ms before stimulus onset was performed.…”

Section: Methodsmentioning

confidence: 99%

Scene Identification and Emotional Response: Which Spatial Frequencies Are Critical?

Cesarei

Codispoti²

2011

J. Neurosci.

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Emotional responses are regulated by basic motivational systems (appetitive and defensive), which allow for adaptive behavior when opportunities and threats are detected. It has been suggested that specific ranges of spatial frequencies of the visual input may contain information that is diagnostic for discriminating emotionally relevant from less relevant contents, and that specialized neural modules may analyze these spatial frequencies to allow efficient detection and response to life-threatening or life-sustaining stimuli. However, there is no evidence supporting this possibility regarding natural scenes, which are highly varied in terms of pictorial composition. The present study examines how low and high spatial frequency filtering affects the understanding of natural scene contents and modulates the amplitude of the late positive potential (LPP), a well-known component of the event-related potentials that reflects motivational significance. The content of an initially degraded (low-or high-passed) picture was progressively revealed in a sequence of steps by adding high or low spatial frequencies. At each step, human participants reported whether they identified the gist of the image. The results showed that the affective modulation of the LPP varied with picture identification similarly for low-passed and high-passed pictures. The engagement of corticolimbic appetitive and defensive systems, reflected in the LPP affective modulation, varied with picture identification, and did not critically or preferentially depend on either low or high spatial frequencies.

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Section: Methodsmentioning

confidence: 99%

Scene Identification and Emotional Response: Which Spatial Frequencies Are Critical?

Cesarei

Codispoti²

2011

J. Neurosci.

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“…All channels were band-pass filtered online from 0.1 to 100 Hz. Offline reduction was performed using ElectroMagnetic EncephaloGraphy Software (EMEGS; Peyk, De Cesarei, & Junghöfer, 2011) and included low-pass filtering at 40 Hz, artifact detection, sensor interpolation, baseline correction, and conversion to the average reference (Junghöfer, Elbert, Tucker, & Rockstroh, 2000). Stimulus-synchronized epochs were extracted from 100 ms before to 1,200 ms after picture onset and baseline corrected (100 ms prior to stimulus onset).…”

Section: Apparatus and Data Analysismentioning

confidence: 99%

Binding neutral information to emotional contexts: Brain dynamics of long-term recognition memory

Ventura‐Bort

Löw

Wendt

et al. 2015

Cogn Affect Behav Neurosci

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There is abundant evidence in memory research that emotional stimuli are better remembered than neutral stimuli. However, effects of an emotionally charged context on memory for associated neutral elements is also important, particularly in trauma and stress-related disorders, where strong memories are often activated by neutral cues due to their emotional associations. In the present study, we used event-related potentials (ERPs) to investigate long-term recognition memory (1-week delay) for neutral objects that had been paired with emotionally arousing or neutral scenes during encoding. Context effects were clearly evident in the ERPs: An early frontal ERP old/new difference (300-500 ms) was enhanced for objects encoded in unpleasant compared to pleasant and neutral contexts; and a late centralparietal old/new difference (400-700 ms) was observed for objects paired with both pleasant and unpleasant contexts but not for items paired with neutral backgrounds. Interestingly, objects encoded in emotional contexts (and novel objects) also prompted an enhanced frontal early (180-220 ms) positivity compared to objects paired with neutral scenes indicating early perceptual significance. The present data suggest that emotional-particularly unpleasantbackgrounds strengthen memory for items encountered within these contexts and engage automatic and explicit recognition processes. These results could help in understanding binding mechanisms involved in the activation of trauma-related memories by neutral cues.

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“…6) rtMEG is a hardware and software complex for the real-time encephalographic analysis, making it possible to inform the subject about his brain activity during the recording [9]. 7) The program package EMEGS provides various methods to process and analyze encephalograms, while not representing sources on the MRI [10]. 8) A wide spectrum of methods to process the MEG is provided by the NUTMEG software, including graphic representation of sources on an MRI [11].…”

Section: Introductionmentioning

confidence: 99%

Новая методология анализа и представления функциональной структуры мозга человека: MEGMRIAn

Ustinin¹

2014

Math.Biol.Bioinf.

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Abstract. The present software was developed to implement a highly spatiotemporal resolved functional tomography (1mm/1msec), capable of addressing spontaneous and evoked activity at any point in the human brain. Presently the methodology is implemented for the magnetic encephalography data. Data analysis results are embedded into a magnetic resonance image of the head. This image is also used as the head model to calculate the magnetic fields of the equivalent current dipoles, while probe positions correspond to real device coordinates. This methodology allows the superposition of the functional frequency patterns to be represented together with magnetic resonance images. The software computational speed makes it possible to implement the whole data acquisition and imaging cycle fast enough to allow optimal protocol choice in data processing.

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ElectroMagnetoEncephalography Software: Overview and Integration with Other EEG/MEG Toolboxes

Cited by 226 publications

References 14 publications

Scene Identification and Emotional Response: Which Spatial Frequencies Are Critical?

Scene Identification and Emotional Response: Which Spatial Frequencies Are Critical?

Binding neutral information to emotional contexts: Brain dynamics of long-term recognition memory

Новая методология анализа и представления функциональной структуры мозга человека: MEGMRIAn

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